Power plants are essential for energy supply, but their efficiency relies on effective maintenance scheduling. Unplanned downtime and high maintenance costs impact productivity and energy output. This dashboard optimizes maintenance schedules by analyzing historical data, plant age, capacity, energy source, and maintenance history. It helps predict maintenance needs, reduce downtime, and improve cost-efficiency, leading to fewer unplanned outages and longer plant lifespans. The dashboard supports data-driven decisions for better energy management and cost control.

Background
Power plant maintenance is a critical challenge in the energy industry, especially with aging infrastructure and high operational costs. Inefficient maintenance and unplanned downtime lead to increased costs and reduced energy production. Identifying maintenance patterns and optimizing schedules is essential for improving plant efficiency, reducing downtime, and ensuring reliable energy supply.

Problem Statement
Power plant maintenance costs continue to rise, with high-capacity plants facing increased downtime and operational inefficiencies. Despite technological advancements, older plants and large multi-unit plants require more frequent and extensive maintenance, leading to significant financial losses and reduced performance. The challenge lies in optimizing maintenance schedules and improving efficiency to reduce costs and minimize unplanned outages. By tackling this issue, plant operators can improve plant longevity, enhance productivity, and ensure a more reliable energy supply.